Background Work-related musculoskeletal disorders (WMSDs), as one of the major occupational health issues worldwide, have shown an increasing positive rate year by year. Due to the unique demands of work, operating room nurses exhibit a higher positive rate of WMSDs compared to other occupational groups, necessitating active attention and intervention. Objective To estimate the prevalence of WMSDs among operating room nurses in tertiary hospitals, explore the characteristics and latent categories of WMSDs, and analyze the influencing factors associated with the occurrence of WMSDs. Method Using a randomized cluster sampling method, operating room nurses from nine tertiary hospitals in Urumqi were selected as study participants between December 2023 and January 2024. Data were collected through a general information questionnaire, an ergonomic questionnaire for operating room nurses, and the Chinese Musculoskeletal Disorders Questionnaire. Latent class analysis was employed to examine the patterns of WMSDs among the nurses, while chi-square test and multinomial logistic regression were utilized to analyze the influencing factors of WMSDs. Result A total of 411 valid questionnaires were collected in this survey. The positive rate of WMSDs among operating room nurses in the tertiary hospitals of Urumqi over the past year was 91.9%. The positive rates, ordered from highest to lowest by body region, were neck (79.1%), shoulders (70.3%), and lower back (68.1%). The operating room nurses were categorized into three distinct groups by latent class analysis: multi-site pain group, neck-shoulder-back pain group, and neck and lower back pain group. The results of the multinomial logistic regression models revealed that gender, job strain level, ergonomic load level in the operating room, and exposure to cold or drafty working conditions or not were significant influencing factors for reporting WMSDs among operating room nurses. Specifically, having less than 5 years of work experience, low ergonomic load level, low job strain, and moderate job strain were identified as protective factors against WMSDs. Conversely, exposure to cold or drafty working environments and being female were identified as risk factors for WMSDs. The logistic regression models also indicated that compared to the neck-lower back pain group, the neck-shoulder-back pain group had a higher probability of reporting low job strain (OR=0.168, 95%CI: 0.029, 0.968) and being female (OR=4.847, 95%CI: 2.506, 9.378). In contrast, when comparing to the neck-lower back pain group, the multi-site pain group had a higher probability of reporting, low-level ergonomic workload (OR=0.079, 95%CI: 0.015, 0.412), low job strain (OR=0.019, 95%CI: 0.002, 0.145), moderate job strain (OR=0.080, 95%CI: 0.016, 0.401), high job strain (OR=0.132, 95%CI: 0.027, 0.647), less than 5 years of work experience (OR=0.173, 95%CI: 0.044, 0.683), being female (OR=2.424, 95%CI: 1.130, 5.200), and exposure to cold or drafty working environments (OR=3.277, 95%CI: 1.657, 6.481). Conclusion The positive rate WMSDs among operating room nurses in tertiary hospitals is notably high in Urumqi, with distinct co-occurrence characteristics observed within the population. To mitigate the risk of WMSDs, it is essential to implement targeted health education and prevention training programs tailored to different patterns of WMSDs. Additionally, improving working conditions, optimizing human resource allocation , and other proactive measures should be undertaken. These efforts will effectively reduce the incidence of WMSDs among operating room nurses and safeguard their occupational health.

Objective To investigate the acupoint selection patterns for treating diabetic cardiac autonomic neuropathy(DCAN)using data mining techniques,providing evidence for clinical practice.Methods Literature on acupuncture treatment for DCAN was retrieved from CNKI,Wanfang,VIP,and PubMed.The publication dates of the included literature ranged from the inception of each database to April 2024.Descriptive analysis,association rule analysis,and cluster analysis were performed on acupoint prescriptions,with the selection patterns of meridians and acupoints were summarized.Results A total of 27 articles were included,involving 18 acupoints.The top 10 high-frequency acupoints were Neiguan(PC6),Xinshu(BL15),Pishu(BL20),Zusanli(ST36),Sanyinjiao(SP6),Shenmen(HT7),Taixi(KI3),Lingtai(GV10),Shendao(GV11),and Shenshu(BL23).The primary meridians selected were the bladder meridian of foot-taiyang and the pericardium meridian of hand-jueyin.Specific acupoint categories predominantly included back-shu points and five transport points.Association rule and cluster analyses identified core acupoint combinations centered on Xinshu,Neiguan,Pishu,and Zusanli.Conclusion The core acupoint combination for treating DCAN with acupuncture comprises Xinshu,Neiguan,Pishu,and Zusanli.

Objective To explore the medication rules of Professor Li Huilin in treating Hashimoto's thyroiditis(HT)complicated with hypothyroidism using data mining techniques based on the R language.Methods Prescription data of the patients with HT complicated with hypothyroidism treated by Professor Li Huilin in outpatient clinics from March 2023 to March 2024 were collected.A database was established using Microsoft Excel 2021,and R language was employed to analyze the frequency,efficacy,properties and flavors,and meridian tropism of the medicinals from Chinese herbal prescriptions.Additionally,correlation analysis,association rule analysis,and cluster analysis were performed on the medicines from Chinese herbal prescriptions.Results A total of 57 Chinese herbal prescriptions involving 125 medicinals with 782 medication frequencies were included.The top 10 frequently-used medicinals were Glycyrrhizae Radix et Rhizoma Praeparata cum Melle(Zhigancao),Angelicae Sinensis Radix(Danggui),Atractylodis Macrocephalae Rhizoma(Baizhu),Astragali Radix(Huangqi),Bupleuri Radix(Chaihu),Cinnamomi Ramulus(Guizhi),Leonuri Herba(Yimucao),Paeoniae Radix Alba(Baishao),Poria(Fuling),and Fici Simplicissimae Radix(Wuzhimaotao).Most of the medicinals had therapeutic action of tonifying deficiency.The analysis of properties and flavors showed that the majority of medicinals were mild or warm in nature,and sweet in flavor.The top three meridians having the tropism of medicinals were the liver,lung,and spleen meridians.Correlation analysis identified five strongly-correlated herbal combinations.Association rule mining revealed a core herbal combination consisting of seven medicinals of Zhigancao,Huangqi,Danggui,Chaihu,Codonopsis Radix(Dangshen),Baizhu,and Cyperi Rhizoma(Xiangfu).Cluster analysis of medicinals with a frequency of≥5 yielded five groups of herbal combination.Conclusion For the treatment of HT complicated with hypothyroidism,Professor Li Huilin follows the principle of addressing the root cause of the disease,and focuses on strengthening the spleen and replenishing qi.Moreover,attention is given to soothing the liver and regulating qi,harmonizing qi and blood simultaneously,and treating symptoms and root cause simultaneously.

Objective:To investigate the value of CT quantitative parameters of tumor and spleen in predicting the clinical stage of gastric cancer (Ⅰ/Ⅱ stage and Ⅲ/Ⅳ stage).Methods:This study was a case-control study. The data of 145 patients with gastric cancer confirmed by pathology in the First Affiliated Hospital of Zhengzhou University from February 2019 to June 2021 were retrospectively collected, including 70 cases of Ⅰ/Ⅱ stage and 75 cases of Ⅲ/Ⅳ stage. On the baseline CT images, the tumor related parameters, including tumor thickness, length of tumor, CT attenuation of tumor unenhanced phase, CT attenuation of tumor arterial phase, CT attenuation of tumor venous phase were measured. The spleen related parameters, including splenic thickness, CT attenuation of splenic unenhanced phase, CT attenuation of splenic arterial phase, CT attenuation of splenic venous phase, and standard deviation of CT attenuation (CTsd) in splenic unenhanced phase were also measured. The independent sample t test or Mann-Whitney U test was used to compare the parameters between the Ⅰ/Ⅱ stage and Ⅲ/Ⅳ stage patients. The multi-factor logistic regression analysis was used to find the independent predictors of gastric cancer clinical stage, and establish the combined parameters. The efficiency to the diagnosis of gastric cancer stage of single and combined parameters was evaluated using the operating characteristic curve, and the DeLong test was used to compare the differences of area under the curve (AUC). Results:There were significant differences in tumor thickness, length of tumor, CT attenuation of tumor venous phase, CT attenuation of splenic unenhanced phase, CT attenuation of splenic venous phase, CTsd in splenic unenhanced phase between the Ⅰ/Ⅱ stage and Ⅲ/Ⅳ stage of gastric cancer ( P<0.05). Multivariate analysis showed that tumor thickness ( OR=1.073, 95% CI 1.026-1.123, P=0.002), CT attenuation of splenic venous phase ( OR=1.040, 95% CI 1.011-1.070, P=0.006) and CTsd in splenic unenhanced phase ( OR=1.625, 95% CI 1.330-1.987, P<0.001) were independent risk factors for the clinical stage of gastric cancer and the combined parameters were established. The AUC values of tumor thickness, CT attenuation of splenic venous phase, CTsd in splenic unenhanced phase and combined parameters were 0.655, 0.614, 0.749 and 0.806, respectively. The AUC of combined parameters was higher than those of tumor thickness and CT attenuation of splenic venous phase, and the differences were statistically significant ( Z=3.37, 3.82, both P<0.001). Conclusion:Tumor thickness, CT attenuation of splenic venous phase and CTsd in splenic unenhanced phase are independent risk factors for the clinical stage of gastric cancer, and combined parameters can improve the diagnostic efficiency.

As an increasing number of emerging anti-tumor drugs are approved and marketed,the imperative for clinical safety monitoring and risk information management has grown significantly.Drug-induced neuropathy associated with these drugs exhibit characteristics such as insidious onset,rapid progression,and challenging treatment,ultimately leading to treatment failures.Therefore,a comprehensive understanding of the risk of neuropathy induced by emerging anti-tumor drugs,coupled with risk surveillance and early warning,as well as management and reporting,can significantly reduce the incidence and severity of drug-related diseases.This paper provides a review of the neuropathy caused by emerging anti-tumor drugs,introduces the pharmacovigilance system and risk information management measures in clinical usage,aiming to provide a reference for guiding the rational clinical use and minimizing the incidence of drug-induced diseases.

In order to establish a rapid,specific and sensitive detection method for Streptococcus equi subspecies zooepidemicus(SEZ)and to understand the infection status of SEZ in horses ente-ring China,specific primers were designed and synthesized based on the conserved gene comB of standard strain SEZ(ATCC 43079)in this work.Then,the pMD19-T-comB recombinant plasmid was constructed and used as a standard positive template.After that,the fluorescence-based quantitative PCR(qPCR)detection method based on SYBR Green Ⅰ dye was established.Totally,477 equine entry serum samples from 6 countries,including Netherlands,Belgium,Japan,Germa-ny,Argentina and New Zealand,during 2018 to 2023,were randomly selected and detected for SEZ by the qPCR method.Results showed that the established qPCR method had specific amplification for only SEZ,which illustrated a good specificity.Sensitivity test of the method showed that the limited detection amount was 4.58 X101 copies/μL.And the repeatability test showed that the coef-ficient of variation of intra-batch repeatability was less than 0.5％,while the inter-batch repeat-ability was less than 3.0％,which indicated good repeatability and high stability.Retrospective a-nalysis showed that totally 11 of 477 positive samples were detected,with a relatively low positive rate of 2.31％(11/477).Among them,all the 40 samples from Netherlands in 2018 were negative(0/40).In the samples of 2019,one positive was detected from Belgium(1/20),while all other 36 samples which form Japan and Germany were negative.In the samples of 2021,three samples(3/34)from Japan and one sample(1/20)from Argentina were positive,and all the other 40 samples from the Netherlands were negative.In the samples of 2022,76 samples from Netherlands were all negative.While in the 2023,5(5/126)of 126 samples from Netherlands and one(1/88)of 88 from New Zealand were found positive with SEZ.To summarize,The SYBR Green Ⅰ qPCR method for the diagnosis of SEZ was successfully established,and it could provide necessary technical support for the rapid quarantine of China's entry-exit and port departments,as well as the epidemiological investigation of the disease.

Abstract: Objective To establish a rapid detection assay based on fluorescence recombinase polymerase amplification (RPA) targeting Necator americanus eggs, and to evaluate its efficacy, providing technical support for rapid detection of Necator americanus in fecal samples. Methods The fluorescence RPA primers and probe were designed based on the cox1 gene of Necator americanus and then screened the optimal combination to develop the assay. The genomic DNA of Necator americanus eggs was diluted to 7 concentration gradients including 100 pg/µL, 10 pg/µL, 1 pg/µL, 100 fg/µL, 10 fg/µL, 1 fg/µL, 0.1 fg/µL, to determine the detection limit of the assay. The specificity of the assay was demonstrated by detected genomic DNA from Schistosoma japonicum, Ascaris lumbricoides, Clonorchis sinensis and Fasciola hepatica. A total of 44 fecal samples were collected and DNA extraction was performed, and the modified Kato-Katz method, semi-nest PCR method, and fluorescent RPA method were simultaneously used for detection to evaluate the sensitivity and specificity. Results The established fluorescence RPA assay can specifically amplify a fragment of 194 bp of the Necator americanus cox1 gene within 20 min, with a detection limit of 10 fg/µL. There was no cross-reactivity with Schistosoma japonicum, Ascaris lumbricoides, Clonorchis sinensis, Fasciola hepatica after specificity validation. In 44 fecal samples, 27 positive samples were detected by the fluorescence RPA assay, and 26 positive samples were detected by both the Kato-Katz and the semi-nested PCR. The fluorescence curve of sample number 1 was slightly higher than the negative control in the later stage of the reaction, but did not show a similar trend to the positive control, and was therefore judged to be a suspected negative sample. Compared with the Kato-Katz method and the semi-nest PCR method, The sensitivity of the fluorescent RPA method were 100.00% and the specificity were 94.44%, and the consistency of the detection results was good (Kappa=0.953>0.75). Conclusions The assay based on the fluorescence RPA is an efficient, sensitive and specific technique for detecting Necator americanus and it can be applied for surveillance and early warning of hookworm infection.

Objective:To evaluate the value of preoperative prediction of vessel invasion (VI) of locally advanced gastric cancer by machine learning model based on the venous phase enhanced CT radiomics features.Methods:A retrospective analysis of 296 patients with locally advanced gastric cancer confirmed by pathology in the First Affiliated Hospital of Zhengzhou University from July 2011 to December 2020 was performed. The patients were divided into VI positive group ( n=213) and VI negative group ( n=83) based on pathological results. The data were divided into training set ( n=207) and test set ( n=89) according to the ratio of 7∶3 with stratification sampling. The clinical characteristics of patients were recorded, and the independent risk factors of gastric cancer VI were screened by multivariate logistic regression. Pyradiomics software was used to extract radiomic features from the venous phase enhanced CT images, and the minimum absolute shrinkage and selection algorithm (LASSO) was used to screen the features, obtain the optimal feature subset, and establish the radiomics signature. Four machine learning algorithms, including extreme gradient boosting (XGBoost), logistic, naive Bayes (GNB), and support vector machine (SVM) models, were used to build prediction models for the radiomics signature and the screened clinical independent risk factors. The efficacy of the model in predicting gastric cancer VI was evaluated by the receiver operating characteristic curve. Results:The degree of differentiation (OR=13.651, 95%CI 7.265-25.650, P=0.003), Lauren′s classification (OR=1.349, 95%CI 1.011-1.799, P=0.042) and CA199 (OR=1.796, 95%CI 1.406-2.186, P=0.044) were independent risk factors for predicting the VI of locally advanced gastric cancer. Based on the venous phase enhanced CT images, 864 quantitative features were extracted, and 18 best constructed radiomics signature were selected by LASSO. In the training set, the area under the curve (AUC) of XGBoost, logistic, GNB and SVM models for predicting gastric cancer VI were 0.914 (95%CI 0.875-0.953), 0.897 (95%CI 0.853-0.940), 0.880 (95%CI 0.832-0.928) and 0.814 (95%CI 0.755-0.873), respectively, and in the test set were 0.870 (95%CI 0.769-0.971), 0.877 (95%CI 0.788-0.964), 0.859 (95%CI 0.755-0.961) and 0.773 (95%CI 0.647-0.898). The logistic model had the largest AUC in the test set. Conclusions:The machine learning model based on the venous phase enhanced CT radiomics features has high efficacy in predicting the VI of locally advanced gastric cancer before the operation, and the logistic model demonstrates the best diagnostic efficacy.

Paridis Rhizoma， a traditional valuable Chinese herbal medicine， has the functions of clearing heat and removing toxin， relieving edema and pain， cooling liver and calming convulsion， which can be used to treat various diseases such as mumps， abscess， burn， bleeding， and tumor. It has been used in folk medicine for a long time and is the main raw material of various Chinese patent medicines such as Gongxuening Capsules and Yunnan Baiyao. Polyphyllin Ⅰ， an isospirostanol saponin and one of the main active components in Paridis Rhizoma， is distributed in the rhizome， pericarp， and leaves of Paris polyphylla. With high polarity， polyphyllin Ⅰ is mainly extracted by n-butanol extraction and macroporous adsorption resin chromatography， separated by silica gel column chromatography and preparative high performance liquid chromatography， and purified with the combination of methods. With anti-tumor， anti-inflammatory， antibacterial， and anti-virus effects， it is generally employed to treat liver cancer， lung cancer， gastric cancer and other cancers as well as arthritis， influenza， sore toxin， and bacterial infection. However， polyphyllin Ⅰ may cause stomach irritation， hemolysis， liver damage， kidney damage， heart damage， and other adverse reactions. Pharmacokinetic studies show that it has problems such as low bioavailability and poor intestinal absorption and permeability， which affect the clinical application of polyphyllin Ⅰ. This paper summarizes the research on the plant sources， extraction and separation methods， pharmacological effects， adverse reactions， and pharmacokinetics of polyphyllin Ⅰ in recent years， which is expected to provide a reference for the rational clinical application and other in-depth research work of polyphyllin Ⅰ.

Objective:To improve the prognosis stratification, especially early mortality(EM), of elderly patients with newly diagnosed multiple myeloma(NDMM).Methods:In this retrospective study, univariate and multivariate Cox regression analysis were conducted to identify the independent prognostic factors associated with overall survival(OS)and the chi-square test and multivariate Logistic analysis were used to identify the prognostic factors associated with EM in 223 elderly patients(age≥65 years)with NDMM from three centers in the country.Results:Increased NT-pro-BNP(≥300 pg/ml), ECOG-PS≥2 and stage Ⅲ R-ISS were identified as three independent adverse prognostic factors of OS.The rates of EM3, EM6, EM12 and EM24 were 12.1%, 20.1%, 32.2% and 60%, respectively.The most common cause for EM6(particularly EM3)was disease-related complications resulting from ineligibility for treatment due to poor physical performance, severe organ dysfunction or treatment discontinuation due to treatment intolerance, while the most common cause for EM12(particularly EM24)was disease progression or relapse mainly as a result of inadequate treatment.R-ISS staging failed to predict EM, while decreased eGFR, ECOG-PS≥2, and increased NT-pro-BNP were able to estimate the risk of EM, with increased NT-pro-BNP as a common independent factor for EM12( P=0.03)and EM24( P=0.015). Conclusions:R-ISS staging, which primarily reflects MM biology, cannot predict EM.However, factors such as NT-pro-BNP, eGFR and ECOG-PS associated with frailty and impairment of organ functions can be used to estimate the risk of EM, among which NT-pro-BNP may be the most important independent factor for EM.Therefore, incorporation of these frailty-related biomarkers into R-ISS staging may be able to more precisely estimate the prognosis and particularly early death of elderly patients with NDMM.